Motion Aided Inertial Navigation System Calibration for In-Drilling Alignment

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dc.contributor.advisorMintchev, Martin
dc.contributor.authorUrsenbach, Nathan Kelly
dc.contributor.committeememberMaundy, Brent
dc.contributor.committeememberNielsen, Jorgen
dc.date2022-02
dc.date.accessioned2022-01-27T22:07:46Z
dc.date.available2022-01-27T22:07:46Z
dc.date.issued2022-01
dc.description.abstractAzimuth survey accuracy is fundamental to directional drilling operations. Industry standard magnetic surveys are limited by interference, and gyroscopic surveys are time intensive or lose accuracy over time due to measurement drift. Alternative solutions are constantly sought. Inertial navigation system (INS) based technologies are not susceptible to external interference, however measurement errors accumulate leading to uncertainty about the true wellbore trajectory to grow exponentially over time. Periodic calibration methods such as zero-velocity update (ZUPT) reduce the rate of error accumulation in INS but with limited success due to a static error model. This work presents a dynamic INS calibration method for measurement-while-drilling (MWD) known as in-drilling alignment (IDA). This method expands on motion aided INS calibration techniques and makes use of controlled motion while the bottom-hole assembly (BHA) is stationary. During this time, linear and rotary motions are induced on the inertial measurement unit (IMU) by electrical actuators. The induced motion is precisely measured by independent sensors. The measured motions and IMU samples become the input to a two-stage inertial navigation system (INS). First, the coarse alignment stage uses equations of motion and the sensor measurements to update the INS states. Next, the extended Kalman filter (EKF) based fine alignment stage takes the measured actuator motion and coarse alignment results to predict the measurement error states in the INS. This work addresses the limitations in industry standard azimuth survey. A method is presented for overcoming these limitations using IDA. The coarse and fine alignment INS stages are presented including a derivation of a novel error model for the EKF. The behavior of the system is investigated using experimental results from a laboratory scale device.en_US
dc.identifier.citationUrsenbach, N. K. (2022). Motion aided inertial navigation system calibration for in-drilling alignment (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39554
dc.identifier.urihttp://hdl.handle.net/1880/114343
dc.language.isoengen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectinertial navigationen_US
dc.subjectextended kalman filteren_US
dc.subjectdirectional drillingen_US
dc.subjectmeasurement while drillingen_US
dc.subjectMWDen_US
dc.subject.classificationEngineering--Electronics and Electricalen_US
dc.titleMotion Aided Inertial Navigation System Calibration for In-Drilling Alignmenten_US
dc.typemaster thesisen_US
thesis.degree.disciplineEngineering – Electrical & Computeren_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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